Quantum computers promise enormous computational power, but the nature of quantum states makes computation and data ...

Similar analogies exist in the area of autonomous vehicles. Overall, machine learning seems to define the notion of probabilistic algorithms in computer science in a similar manner as quantum physics.

It doesn’t take much to make machine-learning algorithms go awry The rise of large-language models could make the problem worse ...

Machine learning is hard. Algorithms in a particular use case often either don't work or don't work well enough, leading to some serious debugging. And finding the perfect algorithm–the set of ...

The labeled data is fed to computer algorithms, teaching the algorithms what to look for. After ingesting millions of labeled images, the algorithms become expert at recognizing what they have ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...

Learning algorithms already make a lot of important decisions every day, from who gets credit to who gets interviewed for a job to who gets flagged as a potential terrorist. And they make mistakes.

That’s what algorithms provide for society: a shortcut to getting a computer to do something it normally couldn’t. Algorithms provide the instructions for almost any AI system you can think of: ...

The field of online algorithms focuses on developing and analyzing such systems, and ensuring that they are "competitive" against the best solution in hindsight. While online algorithms have been ...

Machine learning is a branch of artificial intelligence that uses computer algorithms to solve problems, improving automatically through experience over time. In this case, computers make predictions ...